Business and consumer records are typically contained in databases and other forms of data repositories. Typical databases may contain records such as credit histories, driving records, demographic data, customer data, marketing data, name and address information, bank account information, medical data, court records, securities transactions, and so on. Virtually any type of information may be contained in any such database.
The information contained in such data repositories, however, is generally not static, but is continually changing. For example, account balances may vary from day to day. Individuals change their names, or move to a new city. Businesses expand and add locations, are acquired or divested, or, unfortunately, may go out of business. As a consequence, it is not only important to continually update the appropriate databases with current information, it is also important to track the sources of the updated information, and the likelihood that such changes have, in fact, occurred.
In the prior art, however, when such records are updated, the previous information may be lost. Typically in database management systems, when an update occurs, an older record is merged into the newer record and then may be deleted or purged. The updated information may be inaccurate or erroneous, however, with the accurate data now lost due to the record merger process. In addition, any historical data associated with the merged record may also be lost, including a loss of corresponding source information and other information which pertains to the credibility of the data. In other prior art system, the historical data may be archived and unavailable for use in current data processing tasks.
As a consequence, a need remains for a method, system and software which provides the capability for appropriate mergers of business records, but which also preserves all associated historical data, including source information and merge history, and provides for such historical data to be available in real time for use in current processing tasks, such as searching and matching processes.